Search system and methods with integration of user annotations from a trust network

Abstract

Computer systems and methods incorporate user annotations (metadata) regarding various pages or sites, including annotations by a querying user and by members of a trust network defined for the querying user into search and browsing of a corpus such as the World Wide Web. A trust network is defined for each user, and annotations by any member of a first user's trust network are made visible to the first user during search and / or browsing of the corpus. Users can also limit searches to content annotated by members of their trust networks or by members of a community selected by the user.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS[0001]This application claims the benefit of the following two U.S. Provisional Patent Applications:[0002]Application No. 60 / 553,577, filed Mar. 15, 2004, entitled “Search Systems and Methods with Integration of User Judgments Including Trust Networks”; and[0003]Application No. 60 / 623,282, filed Oct. 28, 2004, entitled “Search Systems and Methods with Integration of User Judgments Including Trust Networks.”The respective disclosures of these applications are incorporated herein by reference for all purposes.[0004]The present disclosure is related to commonly-owned co-pending U.S. patent application Ser. No. 11 / 081,860, filed Mar. 15, 2005, entitled “Search Systems and Methods with Integration of User Annotations,” the disclosure of which is incorporated herein by reference for all purposes.BACKGROUND OF THE INVENTION[0005]The present invention relates in general to searching a corpus of documents, and in particular to search systems and method...

AI Technical Summary

Benefits of technology

[0014]Embodiments of the present invention provide search systems and methods incorporating user judgment information regarding various pages or sites. This information may include judgments from the querying user as well as from other users selected by the querying user as members of his or her “trust network” or some other grouping of users identified by the querying user. For example, in some embodiments, each user who participates in a content annotation system can define a list of friends, where each friend is another user of the system whose annotations the first user would like to share; based on the lists of friends defined by various participating users, a trust network is defined for each user. In other embodiments, a trust network for a user is defined as including members of a well-defined community to which the user belongs. Regardless of how the trust network is defined, annotations by any member of a querying user's trust network can be integrated into the results of subsequent searches of the corpus by the querying user and can also be used in various ways to enhance the querying user's experience of browsing the corpus. In other embodiments, a querying user might specify members of a predefined community (of which the user might or might not be a member), and annotations by any member of that community can be integrated into search results for the querying user and can also be used to enhance the querying user's browsing experience.

Problems solved by technology

Frequently, a query will return such a large number of hits that it is impossible for a user to explore all of the hits in a reasonable time.

If the first few links a user follows fail to lead to relevant content, the user will often give up on the search and possibly on the search service provider, even though relevant content might have been available farther down the list.

This proved inadequate, and algorithms in use today typically incorporate other information, such as the number of other sites on the Web that link to a given hit page (which reflects how useful other content providers think the hit page is), in addition to the presence of search terms on the hit page itself.

Existing algorithms, however, generally do not take into account preferences of individual users.

Thus, a site that satisfies one user (or many users) might not satisfy the next user who enters the same query, and that user might still give up in frustration.

While bookmarking can be helpful, this tool also has its limitations.

For instance, even with folders it can be difficult for a user to remember which bookmarked page had a particular item of information that the user might be looking for at a given time.

Also, existing bookmarking tools generally do not help the user identify whether he (or she) has already bookmarked a given page, nor do they provide any facilities for searching bookmarked information.

Further, existing bookmarking technologies do not provide easy ways for users to share their bookmarks with other users.

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